The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 01, 2019

Filed:

Sep. 23, 2016
Applicant:

Conduent Business Services, Llc, Dallas, TX (US);

Inventors:

Gurulingesh Raravi, Bangalore, IN;

Shruti Kunde, Mumbai, IN;

Sharanya Eswaran, Bangalore, IN;

Deepthi Chander, Cochin, IN;

Nimmi Rangaswamy, Medak, IN;

Joydeep Banerjee, Tempe, AZ (US);

Sindhu Kiranmai Ernala, Telangana, IN;

Meeralakshmi Radhakrishnan, Kerala, IN;

Priyanka Sharma, Rajasthan, IN;

Assignee:

Conduent Business Services, LLC, Florham Park, NJ (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 30/06 (2012.01); G06Q 30/02 (2012.01); H04L 29/08 (2006.01); G06Q 50/00 (2012.01);
U.S. Cl.
CPC ...
G06Q 30/0631 (2013.01); G06Q 30/0251 (2013.01); G06Q 30/0255 (2013.01); G06Q 30/0257 (2013.01); G06Q 30/0261 (2013.01); H04L 67/22 (2013.01); G06Q 50/01 (2013.01);
Abstract

The present disclosure discloses methods and systems for enhancing shopping experience in physical stores. The method includes receiving at least one persona associated with a user based on one or more of: ethnographic data obtained from a user, demographic data associated with the user, buying behavioral data associated with the user, and social networking data associated with the user. After this, one or more historical activities of the user inside one or more physical stores are received. Also, one or more constraints associated with the user are received. Once received, the at least one persona, the one or more constraints, and the one or more historical activities are analyzed to generate a pre-defined number of personalized recommendations. Finally, the personalized recommendations are displayed to the user within a window of a user interface.


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